Data Science and Engineering and Artificial Intelligence
The objective of this area is to contribute to exploit the interactions of data science and engineering techniques with artificial intelligence methods (metaheuristics and machine and deep learning) towards explicable decisions, and to propose new techniques and methodologies in fields like optimization.
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Research Topics
- Data Management and Processing Scalability.
- IoT Data Ingestion.
- Real Time Data Processing and Unstructured Data Management.
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Researchers
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Research Topics
- Data Profiling.
- Data Representation.
- Data Acquisition.
- Data Curation.
- Data Quality.
- Data Veracity.
- Data Integration.
- Semantic Annotation.
- Semantic Reconciliation.
- Semantic Integration.
- Semantic Reasoning.
- Metadata, Context and Domain Semantics.
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Researchers
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Research Topics
- AutoML.
- Inteligencia Artificial para Computación y Comunicaciones Sostenibles.
- Sistemas Inteligentes Distribuidos y Ubicuos.
- IA en Computadoras Cuánticas.
- Modelado Predictivo, Modelado Prescriptivo, Explicable, Confiable y Aprendizaje Automático Ético.
- Aprendizaje Automático como servicio. Aprendizaje Automático Escalable.
- Ensemble Learning, Ingeniería de Características.
- Análisis de DEA.
- Lenguaje de Procesamiento Natural.
- Modelo Métrico y Validación.
- Ajuste de hiperparámetros.
- Visualización.
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Researchers
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Research Topics
- 5G and Intelligent Systems.
- Memetic Computing.
- Multidisciplinary Optimization.
- Optimization and Machine Learning.
- Multi-objective Optimization.
- Large-Scale Optimization.
- Memetic Computing, HPC and Big Data Optimization.
- Automatic Metaheuristic Configuration and Design.
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Researchers
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Research Topics
- Supervised Machine Learning
- Unsupervised Machine Learning
- Self and Semi-Supervised Machine Learning
- Data Visualisation
- Automatic anomaly detection
- Content Based Image Retrieval
- Computer Vision
- Pattern Recognition
- Image Processing
- Neural Rendering
- Deep learning
- Generative Artificial Intelligence
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